Fog is the phenomenon that water vapor in the atmosphere is condensed and floats around the surface of the earth. Since the fog has a particle larger than that of air, light is more scattered and an image obtained under the fog has reduced contrast and chroma due to the scattering of light.
The image under the fog has low contrast and low color fidelity and thus accurate object recognition under the fog is impossible.
An existing technology for removing fog in an image based on dark channel prior (DCP) removes fog using a transmission map depending on the following Equation 1 or Equation 2. In this case, as defogging parameters, A is set to be a brightest pixel value of an image or a brightness value corresponding to a dark channel of 0.01% and w is set to be a fixed value.T=1−w×min(min(RGB/A))  [Equation 1]T=1−w×med(min(RGB/A))  [Equation 2]
In the Equations 1 and 2, T means a transmission map which represents a scattering degree of light depending on a distance and w means a weight.
Therefore, the existing technology of removing fog in an image sets the defogging parameters without considering a density of fog and therefore causes deterioration in defogging performance.
In particular, the existing technology of removing fog in an image have no effect on a side mirrorless system which provides a rear side image of a vehicle to a driver through a display without side mirrors.